Search Results for author: Alexander Lalejini

Found 13 papers, 6 papers with code

Runtime phylogenetic analysis enables extreme subsampling for test-based problems

no code implementations2 Feb 2024 Alexander Lalejini, Marcos Sanson, Jack Garbus, Matthew Andres Moreno, Emily Dolson

We introduce phylogeny-informed subsampling, a new class of subsampling methods that exploit runtime phylogenetic analyses for solving test-based problems.

Program Synthesis

Reachability Analysis for Lexicase Selection via Community Assembly Graphs

no code implementations20 Sep 2023 Emily Dolson, Alexander Lalejini

We then demonstrate that this approach can be successfully applied to a complex genetic programming problem.

Evolutionary Algorithms

Phylogeny-informed fitness estimation

no code implementations6 Jun 2023 Alexander Lalejini, Matthew Andres Moreno, Jose Guadalupe Hernandez, Emily Dolson

Thus far, phylogenetic analyses have primarily been applied as post-hoc analyses used to deepen our understanding of existing evolutionary algorithms.

Evolutionary Algorithms

Analyzing the Interaction Between Down-Sampling and Selection

no code implementations14 Apr 2023 Ryan Boldi, Ashley Bao, Martin Briesch, Thomas Helmuth, Dominik Sobania, Lee Spector, Alexander Lalejini

We verified that down-sampling can benefit the problem-solving success of both fitness-proportionate and tournament selection.

Program Synthesis Symbolic Regression

A Static Analysis of Informed Down-Samples

no code implementations4 Apr 2023 Ryan Boldi, Alexander Lalejini, Thomas Helmuth, Lee Spector

We present an analysis of the loss of population-level test coverage induced by different down-sampling strategies when combined with lexicase selection.

Informed Down-Sampled Lexicase Selection: Identifying productive training cases for efficient problem solving

no code implementations4 Jan 2023 Ryan Boldi, Martin Briesch, Dominik Sobania, Alexander Lalejini, Thomas Helmuth, Franz Rothlauf, Charles Ofria, Lee Spector

Random down-sampled lexicase selection evaluates individuals on only a random subset of the training cases allowing for more individuals to be explored with the same amount of program executions.

Program Synthesis

A suite of diagnostic metrics for characterizing selection schemes

2 code implementations29 Apr 2022 Jose Guadalupe Hernandez, Alexander Lalejini, Charles Ofria

We consider exploitation both with and without constraints, and we divide exploration into two aspects: diversity exploration (the ability to simultaneously explore multiple pathways) and valley-crossing exploration (the ability to cross wider and wider fitness valleys).

Evolutionary Algorithms

What can phylogenetic metrics tell us about useful diversity in evolutionary algorithms?

1 code implementation28 Aug 2021 Jose Guadalupe Hernandez, Alexander Lalejini, Emily Dolson

While these metrics are informative, we hypothesize that other diversity metrics are more strongly predictive of success.

Evolutionary Algorithms

Matchmaker, Matchmaker, Make Me a Match: Geometric, Variational, and Evolutionary Implications of Criteria for Tag Affinity

1 code implementation10 Aug 2021 Matthew Andres Moreno, Alexander Lalejini, Charles Ofria

Genetic programming and artificial life systems commonly employ tag-matching schemes to determine interactions between model components.

Artificial Life TAG

SignalGP-Lite: Event Driven Genetic Programming Library for Large-Scale Artificial Life Applications

no code implementations1 Aug 2021 Matthew Andres Moreno, Santiago Rodriguez Papa, Alexander Lalejini, Charles Ofria

Event-driven genetic programming representations have been shown to outperform traditional imperative representations on interaction-intensive problems.

Artificial Life Benchmarking +1

An Exploration of Exploration: Measuring the ability of lexicase selection to find obscure pathways to optimality

1 code implementation20 Jul 2021 Jose Guadalupe Hernandez, Alexander Lalejini, Charles Ofria

We use our exploration diagnostic to investigate the exploratory capacity of lexicase selection and several of its variants: epsilon lexicase, down-sampled lexicase, cohort lexicase, and novelty-lexicase.

Benchmarking

Evolving Event-driven Programs with SignalGP

1 code implementation15 Apr 2018 Alexander Lalejini, Charles Ofria

We present SignalGP, a new genetic programming (GP) technique designed to incorporate the event-driven programming paradigm into computational evolution's toolbox.

Philosophy TAG

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